The algorithm is executed on a few sample images that span the range of
imaging situations the system is expected to deal with. The recognition module
results of the algorithm are omitted for these calculations since we are only
interested in the localization effectiveness. Figures ,
, , and contain sample
images with the detected feature points marked in white.

In Figure (a) the face is localized even though it is in a
non-frontal pose and despite the thin veil that covers it.
Figure (b) shows the localization of a face despite numerous
other faces in the image. Figure (a) shows the localization of
a blurry face with a large out-of-plane rotation and significant background
data. Figure (b) shows the successful localization of a face
with a beard and glasses which do not pose a problem for the algorithm.
Additionally, the face is leaning backwards slightly.
Figure (a) contains a localized face with a mustache and
dishevelled hair. Figure (b) contains a face with thick
glasses. Figure (a) shows the localization of a face with a
large in-plane rotation and unusual lighting. Figure (b)
depicts a face which is situated in a complex background, under unusual
lighting, with in-plane rotation and at a small scale.
Figure (c) depicts the localization of a face with dark skin
against a bright background. Note the algorithm's ability to localize the
faces in these everyday images despite variations in pose, expressions, facial
paraphernalia, lighting and background clutter.